Contact

Contact

For the possibility of internships or lab visits, please contact Mario Senden via mario.senden@maastrichtuniversity.nl


Curriculum vitae


Department of Cognitive Neuroscience

Maastricht University

Oxfordlaan 55
6229EV Maastricht





Department of Cognitive Neuroscience

Maastricht University

Oxfordlaan 55
6229EV Maastricht



Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling


Journal article


Danny da Costa, Lukas Kornemann, R. Goebel, M. Senden
bioRxiv, 2023

Semantic Scholar DOI
Cite

Cite

APA   Click to copy
da Costa, D., Kornemann, L., Goebel, R., & Senden, M. (2023). Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling. BioRxiv.


Chicago/Turabian   Click to copy
Costa, Danny da, Lukas Kornemann, R. Goebel, and M. Senden. “Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling.” bioRxiv (2023).


MLA   Click to copy
da Costa, Danny, et al. “Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling.” BioRxiv, 2023.


BibTeX   Click to copy

@article{danny2023a,
  title = {Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling},
  year = {2023},
  journal = {bioRxiv},
  author = {da Costa, Danny and Kornemann, Lukas and Goebel, R. and Senden, M.}
}

Abstract

Primate visual cortex exhibits key organizational principles: Cortical magnification, eccentricity-dependent receptive field size and spatial frequency tuning as well as radial bias. We provide compelling evidence that these principles arise from the interplay of the non-uniform distribution of retinal ganglion cells (RGCs), and a quasi-uniform convergence rate from the retina to the cortex. We show that convolutional neural networks (CNNs) outfitted with a retinal sampling layer, which resamples images according to retinal ganglion cell density, develop these organizational principles. Surprisingly, our results indicate that radial bias is spatial-frequency dependent and only manifests for high spatial frequencies. For low spatial frequencies, the bias shifts towards orthogonal orientations. These findings introduce a novel hypothesis about the origin of radial bias. Quasi-uniform convergence limits the range of spatial frequencies (in retinal space) that can be resolved, while retinal sampling determines the spatial frequency content throughout the retina.


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